Samuel Hawkins

19 total papers · 975 total citations
14 papers, 718 citations indexed

About

Samuel Hawkins is a scholar working on Radiology, Nuclear Medicine and Imaging, Pulmonary and Respiratory Medicine and Artificial Intelligence. According to data from OpenAlex, Samuel Hawkins has authored 14 papers receiving a total of 718 indexed citations (citations by other indexed papers that have themselves been cited), including 13 papers in Radiology, Nuclear Medicine and Imaging, 10 papers in Pulmonary and Respiratory Medicine and 7 papers in Artificial Intelligence. Recurrent topics in Samuel Hawkins's work include Radiomics and Machine Learning in Medical Imaging (13 papers), Lung Cancer Diagnosis and Treatment (9 papers) and AI in cancer detection (7 papers). Samuel Hawkins is often cited by papers focused on Radiomics and Machine Learning in Medical Imaging (13 papers), Lung Cancer Diagnosis and Treatment (9 papers) and AI in cancer detection (7 papers). Samuel Hawkins collaborates with scholars based in United States, China and Saudi Arabia. Samuel Hawkins's co-authors include Robert J. Gillies, Lawrence Hall, Dmitry B. Goldgof, Matthew B. Schabath, Yoganand Balagurunathan, Rahul Paul, Robert A. Gatenby, Olya Stringfield, Dmitry Cherezov and Dmitry Goldgof and has published in prestigious journals such as Scientific Reports, IEEE Access and Medical Physics.

In The Last Decade

Samuel Hawkins

14 papers receiving 701 citations

Author Peers

Peers are selected by citation overlap in the author's most active subfields. citations · hero ref

Author						Papers	Cites
Samuel Hawkins	635	410	210	165	61	14	718
Roman Zeleznik	716 1.1×	399 1.0×	272 1.3×	183 1.1×	82 1.3×	15	881
Olya Grove	751 1.2×	319 0.8×	161 0.8×	194 1.2×	142 2.3×	9	888
Qiuchang Sun	640 1.0×	196 0.5×	176 0.8×	112 0.7×	92 1.5×	15	743
Yiwen Xu	468 0.7×	390 1.0×	247 1.2×	116 0.7×	128 2.1×	22	793
Hwan-ho Cho	668 1.1×	214 0.5×	161 0.8×	120 0.7×	85 1.4×	29	805
Xingyu Zhao	508 0.8×	244 0.6×	142 0.7×	103 0.6×	69 1.1×	31	653
Mehrdad Oveisi	683 1.1×	238 0.6×	140 0.7×	276 1.7×	42 0.7×	40	860
M Jermoumi	583 0.9×	240 0.6×	115 0.5×	227 1.4×	98 1.6×	9	665
Cristiana Fanciullo	719 1.1×	249 0.6×	140 0.7×	243 1.5×	131 2.1×	10	861
Charlie Alexander Hamm	417 0.7×	151 0.4×	182 0.9×	92 0.6×	69 1.1×	24	657

Countries citing papers authored by Samuel Hawkins

Since Specialization

Citations

This map shows the geographic impact of Samuel Hawkins's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Samuel Hawkins with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Samuel Hawkins more than expected).

Fields of papers citing papers by Samuel Hawkins

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Samuel Hawkins. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Samuel Hawkins. The network helps show where Samuel Hawkins may publish in the future.

Co-authorship network of co-authors of Samuel Hawkins

This figure shows the co-authorship network connecting the top 25 collaborators of Samuel Hawkins. A scholar is included among the top collaborators of Samuel Hawkins based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Samuel Hawkins. Samuel Hawkins is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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